Risk factor interaction analysis method based on SPSS interpretation structure model

Abstract

The invention discloses a risk factor interaction analysis method based on an SPSS interpretation structure model. The risk factor interaction analysis method comprises the steps of identifying related factors; obtaining an incidence matrix by adopting a bivariate analysis algorithm; determining a threshold value, generating an adjacent matrix, and screening the incidence matrix through the threshold value; calculating a reachable matrix; performing hierarchical division on the reachable matrix; and drawing a multistage hierarchical structure model. Through a correlation analysis method, coupling correlation strength difference between risk factors is considered, subjectivity is reduced, actual conditions are better met, a fuzzy interpretation structure model is constructed, qualitative-to-quantitative conversion of mutual relation determination between influence factors is achieved, and rationality and accuracy of an analysis result are ensured. Therefore, the method is high in objectivity, high in reliability, simple and practical.

Description

technical field [0001] The invention specifically relates to a risk factor interaction analysis method based on an SPSS interpretation structure model. Background technique [0002] With the promotion and application of a large number of distributed access and smart grids, it will inevitably have a huge impact on the risk management of the grid. On the one hand, compared with the single forms of power generation such as traditional thermal power, hydropower, and nuclear power generation, renewable clean energy such as wind energy, solar energy, and tidal energy have already been connected to a large number of distributed energy sources from the user side, which will cause risks affecting power grid security. The number of factors is increasing, the unpredictability is strengthened, and the interaction and coupling of various risk factors form uncertain new risks, and the development of the power grid system is becoming more and more complicated. On the other hand, risk fact...

AI Technical Summary

Problems solved by technology

[0014] However, the traditional explanatory structure model only considers whether there is a relationship between risk factors, and the judgment of the relationship between risk factors only has two values ​​of 1 (influence) and 0 (no influence), and does not involve the strength of the relationship.

But in practice, the strength of the interaction between risk factors is different

Moreover, the adjacency matrix is ​​formed by judging whether the risk factors have coupling effects through the expert scoring method, which is highly subjective; finally, it only considers whether there is a relationship between the risk factors, but does not involve the strength of the impact relationship, lacking quantitative analysis

Images